Process Data from Wearable Light Loggers and Optical Radiation Dosimeters


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Documentation for package ‘LightLogR’ version 0.9.2

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add_clusters Find and extract clusters from a dataset
add_Date_col Create a Date column in the dataset
add_photoperiod Calculate photoperiod and boundary times
add_states Add states to a dataset based on groups and start/end times
add_Time_col Create a Time-of-Day column in the dataset
aggregate_Date Aggregate dates to a single day
aggregate_Datetime Aggregate Datetime data
alphaopic.action.spectra Alphaopic (+ photopic) action spectra
barroso_lighting_metrics Circadian lighting metrics from Barroso et al. (2014)
bright_dark_period Brightest or darkest continuous period
Brown2reference Add Brown et al. (2022) reference illuminance to a dataset
Brown_check Check whether a value is within the recommended illuminance/MEDI levels by Brown et al. (2022)
Brown_cut Create a state column that cuts light levels into sections by Brown et al. (2022)
Brown_rec Set the recommended illuminance/MEDI levels by Brown et al. (2022)
centroidLE Centroid of light exposure
count_difftime Counts the Time differences (epochs) per group (in a grouped dataset)
create_Timedata create_Timedata
cut_Datetime Create Datetime bins for visualization and calculation
data2reference Create reference data from other data
Datetime2Time Convert Datetime columns to Time columns
Datetime_breaks Create a (shifted) sequence of Datetimes for axis breaks
Datetime_limits Find or set sensible limits for Datetime axis
disparity_index Disparity index
dominant_epoch Determine the dominant epoch/interval of a dataset
dose Calculate the dose (value·hours)
dst_change_handler Handle jumps in Daylight Savings (DST) that are missing in the data
dst_change_summary Get a summary of groups where a daylight saving time change occurs.
durations Calculate duration of data in each group
duration_above_threshold Duration above/below threshold or within threshold range
exponential_moving_average Exponential moving average filter (EMA)
exp_zero_inflated Add a defined number to a numeric and log transform it
extract_clusters Find and extract clusters from a dataset
extract_gaps Extract gap episodes from the data
extract_metric Add metrics to extracted sSummary
extract_photoperiod Calculate photoperiod and boundary times
extract_states Extract summaries of states
filter_Date Filter Datetimes in a dataset.
filter_Datetime Filter Datetimes in a dataset.
filter_Datetime_multiple Filter multiple times based on a list of arguments.
filter_Time Filter Times in a dataset.
frequency_crossing_threshold Frequency of crossing light threshold
gain.ratio.tables Gain / Gain-ratio tables to normalize counts
gapless_Datetimes Create a gapless sequence of Datetimes
gap_finder Check for and output gaps in a dataset
gap_handler Fill implicit gaps in a light logger dataset
gap_table Tabular summary of data and gaps in all groups
gg_day Create a simple Time-of-Day plot of light logger data, faceted by Date
gg_days Create a simple datetime plot of light logger data, faceted by group
gg_doubleplot Double Plots
gg_gaps Visualize gaps and irregular data
gg_heatmap Plot a heatmap across days and times of day
gg_overview Plot an overview of dataset intervals with implicit missing data
gg_photoperiod Add photoperiods to gg_day() or gg_days() plots
gg_state Add states to gg_day() or gg_days() plots
has_gaps Does a dataset have implicit gaps
has_irregulars Does a dataset have irregular data
import Import a light logger dataset or related data
import_adjustment Adjust device imports or make your own
import_Dataset Import a light logger dataset or related data
import_Statechanges Import data that contain 'Datetimes' of 'Statechanges'
interdaily_stability Interdaily stability (IS)
interval2state Adds a state column to a dataset from interval data
intradaily_variability Intradaily variability (IV)
join_datasets Join similar Datasets
ll_import_expr Get the import expression for a device
log_zero_inflated Add a defined number to a numeric and log transform it
mean_daily Calculate mean daily metrics from daily summary
mean_daily_metric Calculate mean daily metrics from Time Series
midpointCE Midpoint of cumulative light exposure.
normalize_counts Normalize counts between sensor outputs
number_states Number non-consecutive state occurrences
nvRC Non-visual circadian response
nvRC_circadianBias Performance metrics for circadian response
nvRC_circadianDisturbance Performance metrics for circadian response
nvRC_metrics Performance metrics for circadian response
nvRC_relativeAmplitudeError Performance metrics for circadian response
nvRD Non-visual direct response
nvRD_cumulative_response Cumulative non-visual direct response
period_above_threshold Length of longest continuous period above/below threshold
photoperiod Calculate photoperiod and boundary times
pulses_above_threshold Pulses above threshold
remove_partial_data Remove groups that have too few data points
reverse2_trans Create a reverse transformation function specifically for date scales
sample.data.environment Sample of wearable data combined with environmental data
sample.data.irregular Sample of highly irregular wearable data
sc2interval Statechange (sc) Timestamps to Intervals
sleep_int2Brown Recode Sleep/Wake intervals to Brown state intervals
solar_noon Calculate photoperiod and boundary times
spectral_integration Integrate spectral irradiance with optional weighting
spectral_reconstruction Reconstruct spectral irradiance from sensor counts
summarise_numeric Summarize numeric columns in dataframes to means
summarize_numeric Summarize numeric columns in dataframes to means
supported_devices Get all the supported devices in LightLogR
symlog_trans Scale positive and negative values on a log scale
threshold_for_duration Find threshold for given duration
timing_above_threshold Mean/first/last timing above/below threshold.